A simple, effective tool for generating cutouts of objects in astronomical imaging.
What is required are images with valid WCS information, and a catalogue of objects.
For a single image:
python CutoutCreator.py path_to_image.fits object_catalog.fits
For a directory of images:
python CutoutCreator.py path_to_directory/ object_catalog.fits -b
For a directory of images using multiple threads:
python CutoutCreator.py path_to_directory/ object_catalog.fits -b --multi
-s --cutout_size INT Define cutout size (integer). Default cutout size (width and height) is 61
-b Run in batch mode. (The input is treated as a directory instead of a filename)
--multi Run using multithreading. Will only run if batch mode is selected.
-m --mask Mask object cutouts. This will try to remove the light from companion objects from the cutout.
-O --output_subdir STR Generate (if needed) a defined subdirectory to save cutouts.
--ra --dec STR Define catalog column names for right ascension and declination. Defaults are RA and DEC.
--snr FLOAT Define a required signal to noise ratio cutoff (float) that objects must be above in order to save the cutout. This is most effective when masking cutouts.
-i --isolated FLOAT Select a percentage threshold of allowed masked pixels (between 0 and 1) in order to save images. This is useful if one is looking for isolated objects.
--maskparams STR "(FLOAT, FLOAT, INT)" Define the parameters for masking. These are the values nsigma, gauss_width, npixels which define the snr required to be a detected object, the width of the gaussian convolution kernel used in masking, and the minimum number of pixels required for a cluster of pixels to be a detection. These can be adjusted to increase or decrease the severity of the masking procedure.
Note that these tests were run on a somewhat slower partition on my local machine. YMMV.
413 cutouts from a catalog of 68736 potential objects. No masking. 19 seconds
959 cutouts from a catalog of 164342 potential objects. No masking. 39 seconds
413 cutouts from a catalog of 68736 potential objects. Masking applied. 76 seconds
959 cutouts from a catalog of 164342 potential objects. Masking applied. 154 seconds
It can be seen that the amount of time required scales mostly linearly with a larger catalog. Masking drastically increases the time required, by approximately a factor of 4.